Source: https://toddschiller.com/blog/loop-engineering-compounding.html

# Note Loop Engineering: always be compounding

Jul 07, 2026 by
[Todd Schiller](https://toddschiller.com/pages/about.html)

Also posted on
[LinkedIn ↗](https://www.linkedin.com/posts/tschiller_loops-agents-share-7480288109205684224-_yMM/)

Loop engineering for AI agents should raise the floor on each iteration by creating tools and correcting instructions.

AIagentsloop engineeringtoolsinstructions

Loop engineering for AI agents should be about compounding, not repetition.

A weak work loop does the same thing every pass: trigger, execute, review.

A strong work loop leaves the system better than it found it.

Sure, many harnesses now automatically improve via agent memory. However, that's
leaving your work to chance: memory creation is inconsistent, and false
memories degrade performance.

The better way is to edit the loop itself:

- Skills/Instructions: conventions, assumptions, examples, failure modes
- Tools: scripts, workflows, fixtures, test harnesses

With each run, the loop becomes more capable, more reliable, and more
cost-effective.

What are your go-to strategies for compounding?

![Whiteboard-style diagram titled Agent loops should compound. The left panel shows a repeating routine that starts from the same place each time: Trigger, Execute, Review. The right panel shows a compounding routine where loop 1, loop 2, and loop 3 climb upward on a system-improves axis, with orange step-up arrows labeled Refine and gains labeled Task done, plus instruction, and plus tool.](https://toddschiller.com/assets/images/loop-engineering-compounding/loop-engineering-compounding-landscape-ai-whiteboard-2400.png)

More on

- [`#AI`](https://toddschiller.com/tag/ai.html) (12)
- [`#agents`](https://toddschiller.com/tag/agents.html) (5)
- [`#loop engineering`](https://toddschiller.com/tag/loop-engineering.html)
- [`#tools`](https://toddschiller.com/tag/tools.html)
- [`#instructions`](https://toddschiller.com/tag/instructions.html)